• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.11-14
• /
• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.41-52
• /
• 2013

One of the obstacles preventing the Zigbee protocol from being widely used is the excessive power consumption of Zigbee devices in low bandwidth and low power requirement applications. This paper proposes a protocol that resolves the power efficiency problem. The proposed protocol reduces the power consumption of Zigbee devices in beacon-enabled networks without increasing the time taken by Zigbee peripherals to communicate with their coordinator. The proposed protocol utilizes a beacon control mechanism called a "sleep pattern," which is updated based on the previous event statistics. It determines exactly when Zigbee peripherals wake up or sleep. A simulation of the proposed protocol using realistic parameters and an experiment using commercial products yielded similar results, demonstrating that the protocol may be a solution to reduce the power consumption of Zigbee devices.

• Korean Management Science Review
• /
• v.20 no.1
• /
• pp.65-76
• /
• 2003

The increased environmental concerns and the emphasis on recycling are gradually shifting the orientation of municipal solid waste (MSW) management. This paper is designed to evaluate regionalization programs for MSW management system. We developed a mixed intiger network programming (MIP) model to identify environment-friendly, cost-effective expansion plans for regionalization scenarios considered. The MIP model is a dynamic capacity expansion model based on the network flow model that depicts the MSW management cycle. In particular, our model is designed to determine the optimal form of regionalization using binary variables. We apply this model to assess the regionalization program of Seoul Metropolitan City, which includes three scenarios such as 1) districting, 2) regionalization with neighboring self-governing districts, and 3) g1obalization with all districts. We demonstrate how our model can be used to plan the MSW system. The results indicate that optimal regionalization with nearby self-governing districts can eliminate unnecessary landfills and expansions if jurisdictional obstacles are removed.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.223-225
• /
• 2006

A ball moving on a beam is a typical nonlnear dynamic system, which is often adopted to proof test diverse control schemes. Ball and plate system is the extension of the traditional ball and beam problem that moves a metal ball on a rigid plate. In this paper, a trajectory planning and tracking problem is proposed for ball and plate system, which is to control the ball from a point to another without hitting the obstacles. Our scheme is composed of three controllers, TS type optimal path tracking controller, mandani type obstacle avoidance controller and trajectory planning controller that determines the desired trajectory. But this type of construction can give rise to chattering executions. Because the difference of contributions from concurrent controllers can cause behaviors unsmoothly. We propose fuzzy pid supervision control1er to handle this problem.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.446-448
• /
• 1994

This paper proposes some dynamic navigation strategy for a mobile robot among multiple moving obstacles. The control force of the robot which consists of repulsive and attractive force is based on the artificial potential field. The artificial potential fields is derived with position or(and) velocities of the objects. The simulation results shows the properties of the proposed strategies.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.9
• /
• pp.799-808
• /
• 2004

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.44-47
• /
• 1996

Bang-bang control law provides the optimal solution for a minimum-time control problem, but ignores the intermediate path except for the initial and final points. In this paper, a near minimum-time suboptimal fuzzy logic controller is introduced that can control the intermediate path. A dynamic model for a system is established using the average dynamics method of linearization. System model is continuously updated over the control time periods. This makes it suitable for high speed or variable payload applications. Bang-bang control theory is modified and used to derive the preliminary control law. A fuzzy logic algorithm is then applied to adjust and find the best solution. The solution will provide the suboptimal minimum-time control law which can avoid obstacles in the workspace.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.790-793
• /
• 2002

In this paper, dynamic path planning of two mobile robots using a modified Hopfield neural network is studied. An area which excludes obstacles and allows gradually changing of activation level of neurons is derived in each step. Next moving step can be determined by searching the next highest activated neuron. By learning repeatedly, the steps will be generated from starting to goal points. A path will be constructed from these steps. Simulation showed the constructed paths of two mobile robots, which are moving across each other to their goals.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.6
• /
• pp.122-127
• /
• 1996

The achievement of the optimal condition for the task of an industrial articulated robot used in many fields is an important problem to improve productivity. In this paper, a minimum-time trajectory for an articulated robot along the specified path is studied and simulated with a proper example. A general dynamic model of manipulator is represented as a function of path distance. Using this model, the velocity is produced as fast as possible at each point along the path. This minimum-time trajectory planning module together with the existing collision-free path planning modules is utilized to design the optimal path planning of robot in cases where obstacles present.

• Journal of the Korean Society of Industry Convergence
• /
• v.19 no.2
• /
• pp.75-80
• /
• 2016

This study proposes a efficient technology to control the optimal trajectory planning and real-time implementation method which can perform autonomous travelling for unmaned factory automation. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on Route planning and control algorithm, we suggested representation of edge cost, heuristic function, and priority queue management, to make a modified Route planning algorithm. Performance of the proposed algorithm is verified by simulation test.